Jake Luo, Ph.D.

Assistant Professor; Director, Center for Biomedical Data and Language Processing (BioDLP)

[Image] Jake Luo

Northwest Quadrant Building B, Room 6469
Phone: (414) 229-7333
Fax: (414) 229-2619
JakeLuo@uwm.edu

Department

Health Informatics & Administration

Education

  • Postdoctoral Research Scientist, Biomedical Informatics,
    Columbia University, New York, 2012
  • Ph.D., Computer Science, Queen's University, Belfast, UK, 2009
  • M.S., Software Engineering, Xidian University, China, 2004
  • B.S., Electrical Engineering, Xidian University, China, 2004
noacc 5611

Speaker Topics

  • Health Informatics
  • Clinical Research Informatics
  • Text Mining and Information Extraction
  • Natural Language Processing
  • Knowledge Representation and Management
  • Big Data and Predictive Analysis

Interests & Expertise

My primary research interest lies in data-driven predictive analysis using machine-learning algorithms, e.g. data mining, natural language processing, and knowledge representation and modelling. Currently, I am especially interested in investigating how these computing technologies can improve healthcare by providing intelligent decision support for clinicians and researchers.


Recent Publications

Peer-reviewed Publications

Luo, Z., Zhang, G. Q., & Rong, X. (2013). Mining Adverse Event Association in Clinical Trials. AMIA Joint Submits to Translational Science, 112-118.

Luo, Z., Miotto, R., & Weng, C. (2013). A Human-Computer Collaborative Approach to Identifying Common Data Elements in Clinical Trial Eligibility Criteria. Journal of Biomedical Informatics, 46(1), 33-39.

Luo, Z., Johnson, S. B., Lai, A. M., & Weng, C. (2011). Extracting Temporal Constraints from Clinical Research Eligibility Criteria Using Conditional Random Fields. American Medical Informatics Association Annual Symposium (AMIA) (pp. 843-852). Washington, DC.

Weng, C., Wu, X., Luo, Z., Boland, M. R., Theodoratos, D., & Johnson, S. B. (2011). EliXR: An Approach to Eligibility Criteria Extraction and Representation. Journal of the American Medical Informatics Association (JAMIA). Accepted 2011. doi:10.1136/amiajnl-2011-000321, i116-i124.

Luo, Z., Yetisgen-Yildiz, M., & Weng, C. (2011). Dynamic categorization of clinical research eligibility criteria by hierarchical clustering. Journal of Biomedical Informatics (JBI), 44(6), 927-935.

Luo, Z., Johnson, S. B., & Weng, C. (2010). Semi-Automatic Induction of Semantic Classes from Free-Text Clinical Research Eligibility Criteria Using UMLS and Hierarchical Clustering. American Medical Informatics Association Annual Symposium (AMIA) (pp. 487-491). Washington, DC.

Luo, Z., Duffy, R., Johnson, S., & Weng, C. (2010). Corpus-based Approach to Creating a Semantic Lexicon for Clinical Research Eligibility Criteria from UMLS. AMIA Summit on Clinical Research Informatics (AMIA CRI) (pp. 26-31). San Francisco, CA.

Miao, X. F., Luo, Z., & Hong, L. (2009). Routing Protocol Simulation Research Based on SUMO. Computer Engineering, Network and Communications, 37(01), 106-109.

Graham, C., Bell, D., & Luo, Z. (2009). Multi-Agent Reinforcement Learning – An Exploration Using Q-Learning. In: Bramer M, Ellis R, Petridis M, eds. Research and Development in Intelligent Systems XXVI: Springer London; 2009: 293-298.

Wu, Q., Xi, H., Bell, D., Qi, G., & Luo, Z. (2008, October). Incremental Knowledge Base for Uncertain Reasoning. Fifth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 187-192.

Luo, Z., Bell, D., McCollum, B., & Wu, Q. (2008, June). Learning to select relevant perspective in a dynamic environment. IEEE International Joint Conference on Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence).  (pp. 666-673). Hong Kong.

Luo, Z., Bell, D., & McCollum, B. (2008). Discover relevant environment feature using concurrent reinforcement learning. Proceedings of the 23rd AAAI conference on Artificial intelligence - Volume 3 (pp. 1816-1819). Chicago, Illinois.

Wu, Q., Bell, D., Huang, X., Khokhar, R. H., Qi, G. &, Luo, Z. (2007). Autonomous Robot Control Using Evidential Reasoning. Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) (pp. 550-554).

Luo, Z., Bell, D., & McCollum, B. (2007). Skill Combination for Reinforcement Learning. Proceedings of the International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'07) (pp. 87-96).

Peer-Reviewed Posters and Abstracts

Luo, Z., Sahoo, S., & Zhang, G. Q. (2012). ICaRe: A Web Services-based Unified Informatics Portal for the Cleveland CTSC. CTSA Informatics Key Function Committee Meeting; Chicago, 2012.

Luo, Z., Sahoo, S., & Zhang, G. Q. (2012). A Pipeline for Rendering and Analyzing Large Institutional Research Networks. CTSA Informatics Key Function Committee Meeting; Chicago, 2012.

Weng, C., & Luo, Z. (2010). Dynamic Categorization of Clinical Research Eligibility Criteria. Proc of AMIA Fall Symp. 2010. 306.


Honors & Awards

  • Best student paper finalist, AMIA Annual Symposium , 2011
  • Distinguished paper award (co-author), AMIA CRI submit, 2011
  • School travel scholarship, Queen’s University Belfast, 2008

Professional Membership

  • Member of the American Medical Informatics Association (AMIA), 2009-present
  • Member of Association for Advancement of Artificial Intelligence (AAAI), 2006-2010
  • Member of Institute of Electrical and Electronics Engineers (IEEE), 2008-2009

Courses Taught

  • Fundamental programming practice class (Java)
  • Advanced programming class